Fully automatic segmentation of abdominal organs from CT images using fast marching methods

Proceedings - IEEE Symposium on Computer-Based Medical Systems

Volumn , Issue , 2008, Pages 554-559

  Campadelli, Paola ^a   Casiraghi, Elena ^a   Pratissoli, Stella ^a  

^a UNIVERSITY OF MILAN   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DIAGNOSTIC RADIOGRAPHY; ELECTRIC INSTRUMENT TRANSFORMERS; HEALTH; IMAGE ENHANCEMENT; IMAGE PROCESSING; IMAGING SYSTEMS; IMAGING TECHNIQUES; MEDICAL IMAGING; OPTICAL DATA PROCESSING; TECHNICAL PRESENTATIONS; THREE DIMENSIONAL; TOMOGRAPHY; VOLUME RENDERING;

ABDOMINAL ORGANS; AUTOMATIC DIAGNOSIS; AUTOMATIC SEGMENTATIONS; COMPUTED TOMOGRAPHY IMAGES; COMPUTER-BASED MEDICAL SYSTEMS; CT IMAGING; FAST MARCHING; FAST MARCHING METHODS; GRAY LEVELS; INTERNATIONAL SYMPOSIUM; MANUAL SEGMENTATION; MEDICAL IMAGE PROCESSING; OPEN PROBLEMS; SEGMENTATION SCHEME; SYSTEM PERFORMANCES;

COMPUTERIZED TOMOGRAPHY;

EID: 51849100898     PISSN: 10637125     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMS.2008.9     Document Type: Conference Paper

References (13)

1. P. Campadelli and E. Casiraghi. Liver segmentation from CT scans: A survey. Proceedings of Fourth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2007), Portofino, 7-10 July 2007.
2. P. Campadelli, E. Casiraghi, and G. Lombardi. Automatic liver segmentation from abdominal CT scans. Proocedings of 14th International Conference on Image Analysis and Processing (ICIAP 2007),Modena, September 2007.
3. J. Harms, Bartels, et al. Computerized CT-based 3d visualization technique in living related liver transplantation. Transplantation Proceedings, 37:1059-1062, 2005.
4. H. Lamecker, T. Lange, and M. Seebass. Segmentation of the liver using a 3d statistical shape model. ZIB-Report 04-09, 04-09:1-25, 2004, April.
5. Lee, Chung, et al. Classification of liver diseases from CT images using BP-CMAC Neural Network. Proceedings of 9th International Workshop on Cellular Neural Networks and Their Applications, pages 118-121, 2005.
6. Y. Nakayama, Q. Li, Katsuragawa, et al. Automated hepatic volumetry for living related liver transplantation at multisection CT. Radiology, 240 (3):743-748, 2006, September.
7. P. Perona and J. Malik. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Int., 12(7):629-639, 1990.
8. J. S. R. Malladi and B. Vemuri. Shape modeling with front propagation: a level set approach. IEEE Trans. Pattern Anal. Mach. Int., 17:158-174, 1995.
9. A. Schenk, G. Prause, and H. Peitgen. Efficient semiautomatic segmentation of 3d objes in medical images. Proceedings of Medical image computing and computer-assisted intervention (MICCAI 2000), 1:186-195, 2000.
10. J. Sethian. A fast marching level set method for monotonically advancing fronts. Proc. Nat. Acad. Sci., 93:1591-1595, 1996.
11. J. Sethian and A. Vladimirsky. Ordered upwind methods for static hamilton-jacobi equations. Proc. Nat. Acad. Sci., 98:11069-11074, 2001.
12. J. A. Sethian. Level set methods and fast marching methods. Cambridge Cambridge University Press, 1999.
13. J. Weickert. A review of nonlinear diffusion filtering. Scale-Space Theories in Computer Vision, pages 3-28, 1997.